Measured Soil Properties Research Articles

Changes in vegetation and soil properties across 12 years after afforestation in the hilly-gully region of the Loess Plateau

Vegetation restoration is the primary method used to prevent soil erosion and improve the ecological environment. The objective of this study was to explore how vegetation and soil properties changed over time in natural and artificial vegetation types. We conducted vegetation surveys in four permanent plots over 12 years (2007–2018) and measured soil properties in 2007, 2013, and 2016. The results showed that the change in species composition in natural vegetation was a continuous and progressive process. After approximately ten years of natural herb restoration, trees began to appear and formed sparse forests. In artificial vegetation, the species composition of the undergrowth varied under Robinia pseudoacacia forests during restoration years, and was dominated by Poaceae and annual plants that could tolerate shade and drought. Species composition was stable under Caragana korshinskii shrubs, where the undergrowth was dominated by perennial plants that were similar to natural vegetation. In different vegetation types, species richness, diversity, and herb community cover fluctuated, while the succession rate decreased with the number of restoration years. The soil moisture condition was better in natural vegetation than in artificial vegetation, and could be maintained near the stable field capacity. The soil moisture was supplemented to 280 cm in R. pseudoacacia forests and 320 cm in C. korshinskii shrubs in a year with extreme rainfall, but the dry soil layer returned in the following years. Soil nutrients improved over time, especially in artificial vegetation, which appears to be better than natural vegetation. In general, natural vegetation improved plant community and soil properties. Artificial vegetation only improved soil nutrients, but caused soil desiccation which is difficult to recover. Therefore, the natural vegetation restoration model of sparse forest grassland was better than artificial vegetation model.

The impact of semi‐natural broadleaf woodland and pasture on soil properties and flood discharge

AbstractWoodlands can reduce the risk of rainfall‐generated flooding through increased interception, soil infiltration and available storage. Despite growing evidence, there is still low confidence in using woodlands as a flood mitigation method due to limited empirical data, particularly for broadleaf woodlands. We measured soil properties and streamflow for nine small (<0.2 km2) upland catchments and compared mature semi‐natural broadleaf woodland where no stock grazing occurs to pasture with varied grazing intensity. We compared streamflow across 28 storm events including a 1 in 10‐year event, two 1 in 4‐year events and five 1 in 1.5‐year events, identified over a 13‐month period. We found that semi‐natural broadleaf woodlands reduce specific peak discharge by 23%–60% and peak runoff coefficients by 30%–60% compared with pasture. Response to storm events took 14–50% longer in woodland compared to pasture. These differences in flood response are partly explained by more permeable woodland soils, 11–20 times greater than pasture soil. The more muted response of wooded catchments to storm events is consistent across the storms investigated, including Storm Ciara, a 1 in 10‐year event. Our analysis strengthens the argument that semi‐natural woodlands can reduce rainfall‐generated flooding contributing to the evidence base for natural flood management.

Statistical method for a hydraulic conductivity estimate using empirical formulas

Sediment's hydraulic conductivity is one of the key inputs for estimating solute and water movement in a vadose zone. Laboratory and field measurements are time consuming and subject to substantial inaccuracies. Thus numerous empirical formulas have been adopted to predict hydraulic conductivity from measurable soil properties such as grain size distribution, soil temperature or bulk density. The objective of this study was twofold: (1) assess the hydraulic conductivities calculated from empirical formulas and (2) develop a simple method to estimate hydraulic conductivities for clayey sand sediments. Using sediment samples extracted from irrigation canals in Zitny Ostrov, Southern Slovakia, we evaluated fourteen empirical formulas. Three sets of parameters were assessed using common statistical methods. The sets included computed hydraulic conductivities, logarithmically transformed hydraulic conductivities, and measured values of hydraulic conductivities. Field measurements and laboratory investigations of hydraulic conductivities were performed to supplement our empirical calculations. The three sets of parameters were compared and formed the foundation for developing an original regression equation: Ksat me = 0.019 (LTKsat) 2 + 0.183 (LTKsat) + 4.863an equation that captures the variables with reasonable agreement. The logarithmically transformed and measured values correlated, yielding R2 = 0.945. Thus, the measured values validated our regression equation.

Soil enzyme stoichiometry revealed the changes of soil microbial carbon and phosphorus limitation along an elevational gradient in a Pinus taiwanensis forest of Wuyi Mountains, Southeast China

Understanding changes in soil enzyme activities and ecoenzymatic stoichiometry is important for assessing soil nutrient availability and microbial nutrient limitation in mountain ecosystems. However, the variations of soil microbial nutrient limitation across elevational gradients and its driving factors in subtropical mountain forests are still unclear. In this study, we measured soil properties, microbial biomass, and enzyme activities related to carbon (C), nitrogen (N), and phosphorus (P) cycling in Pinus taiwanensis forests at different altitudes of Wuyi Mountains. By analyzing the enzyme stoichiometric ratio, vector length (VL), and vector angle (VA), the relative energy and nutrient limitation of soil microorganisms and its key regulatory factors were explored. The results showed that β-glucosaminidase (BG) activities increased along the elevational gradient, while the activities of β-N-acetyl glucosaminidase (NAG), leucine aminopeptidase (LAP), acid phosphatase (AcP) and (NAG+LAP)/microbial biomass carbon (MBC) and AcP/MBC showed the opposite trend. Enzyme C/N, enzyme C/P, enzyme N/P, and VL were enhanced with increasing elevation, while VA decreased, indicating a higher degree of microbial P limitation at low elevation and higher C limitation at high elevation. In addition, our results suggested that dissolved organic carbon and microbial biomass phosphorus are critical factors affecting the relative energy and nutrient limitation of soil microorganisms at different elevations. The results would provide a theoretical basis for the responses of soil carbon, nitrogen, and phosphorus availability as well as the relative limitation of microbial energy and nutrition to elevational gradients, and improve our understanding of soil biogeochemical cycle process in subtropical montane forest ecosystems.

Variability and correlation of selected soil attributes and maize yield influenced by tillage systems in mountainous agroecosystem

Soil and topographic variability severely influence agricultural productivity and food security in a mountainous agroecosystem. Understanding these soil spatial disparities are important to optimize suitable land use planning and adoption of appropriate conservation practices to ensure sustainable agricultural productivity in mountainous regions. A field survey and sampling of 108 elevation sites were conducted to assess spatial dynamics and influence of prevalent tillage systems on selected soil attributes and on reported maize (<i>Zea mays</i> L.) grain yield (MGY) in mountainous valleys of Pakistan. Measured soil properties were effective soil depth (ESD), soil penetration resistance (SPR), soil bulk density (SBD), fraction of rock fragments (FRF), soil organic matter (SOM), and soil water holding capacity (SWHC). Additionally, the influence of three existing tillage systems—integrated tillage (IT), bullock tillage (BT), and tractor tillage (TT)—on soil properties and MGY were assessed. Research results showed that ESD, SPR, SBD, FRF, SOM, SWHC, and MGY varied from 15.0 to 40.0 cm, 180.0 to 278.0 psi, 0.9 to 1.7 g cm⁻³, 13.2% to 43.5%, 0.6% to 2.9%, 10.5% to 35.6%, and 4.1 to 10.2 t ha⁻¹, respectively. Differences between soil parameters were significant among the sampling sites studied. Soil properties were found to be strongly associated with each other and with the MGY and were grouped through Pearson correlation, principal component analysis, and heatmap. Moreover, significant variation of soil properties was noted due to the tillage systems adopted by the farmers. The ESD (26.8 cm), SOM (1.4%), SWHC (16.9%), and MGY (7.8 t ha⁻¹) were the highest under IT while the SPR (262.8 psi), SBD (1.6 g cm⁻³), and FRF (38.0%) were the greatest with TT compared to the other tillage systems. Findings of this study are imperative for agriculturists, soil managers, land use planners, and policy makers to identify and implement suitable interventions for sustainable use of agricultural lands to bring economic produce while conserving the mountainous agroecosystem and its resources on sustainable basis.

Modeling and Statistical Evaluations of Unconfined Compressive Strength and Compression Index of the Clay Soils at Various Ranges of Liquid Limit

Abstract A significant stage in geotechnical engineering is to establish geotechnical properties of soil models to predict the most important soil properties such as unconfined compressive strength (UCS) and compression index (Cc) because they are the main parameters in the state design of the footings, pavements, or stability assessment of existing structures or slopes. This study is focused on developing models to predict the compressive strength and Cc for the clay soils as a function of Atterberg limits, natural moisture content, dry density, void ratio, and fine content (passing ≤ 0.075 mm). The UCS of the soils ranged from 24 to 340 kPa and was quite accurately quantified using the laboratory-tested data and data collected from published research studies. The Cc of the soils varied between 0.0878 to 0.8317, which was also correlated as a function of easy measurable soil properties such as Atterberg limits, natural moisture content, density, void ratio, and fine contents (percentage passing sieve number 200). A wide experimental test results (a total of 253 tested soils) were combined with more than 350 data collected from different academic research studies, and total data were statistically analyzed and modeled. In the modeling process, the most relevant parameters affecting the compressive strength and Cc of soils incorporation ratio (6–41 % of moisture content), plasticity index (7–72 %), dry density (11–19 kN/m3), and fine content (0–100 %). According to the correlation determination, mean absolute error, and the root mean square error, the compressive strength and Cc of soil can be well predicted in terms of liquid limit, plasticity index, moisture content, dry density, void ratio, and percentage passing sieve No. 200 (75 µm) using linear simulation techniques. The sensitivity investigation concludes that the dry density and moisture content are the most important parameters for the prediction of the compressive strength and Cc, respectively, with the training data set.

Flood aftermath on soil quality in north central laterites of Kerala

Soil quality mostly refers to the dynamic properties of surface soil (0 to 25 cm) that can be strongly altered by management practices. The study aimed at the assessment of soil quality in the post-flood soils and the findings were quantified by expressing as a function of measurable soil properties. Among the 23 parameters analyzed on 100 geo-referenced soil samples, soil pH, bulk density, available nitrogen (N), phosphorus (P), calcium (Ca), copper (Cu), boron (B) and microbial biomass carbon (MBC) were found as key indicators influencing soil quality. Depending on the contribution of indicators to soil quality they were categorised, scored and finally, weighted indicators were summarised into soil quality index (SQI) using standard formula. The contribution of pH and bulk density was highest to soil quality index while, the lowest contribution was shared by available B. The SQI was highest in Pariyaram Panchayat, where the analytical value of key indicators were near to optimum range and lowest in Meloor due to the poor content of available N and MBC. The deviation in soil quality was measured and expressed in terms of relative soil quality index (RSQI), which was found to be medium in 82% of the samples. Improvement in SQI can be achieved by optimizing the key soil indicators in each site

Predicting wind erosion rate using portable wind tunnel combined with machine learning algorithms in calcareous soils, southern Iran

Wind erosion is a critical factor in land degradation worldwide, particularly in arid and semi-arid regions of southern Iran, which have been severely exposed to wind erosion in the recent years due to climate change and land use changes. The main objective of the present study was to predict the wind erosion rate (WER) using easily measurable soil properties combined with some data mining approaches. For this purpose, the WER was measured at 100 locations with different land uses and soil types in the Fars Province, southern Iran using a portable wind tunnel. The WER was predicted by multiple linear regression (MLR), support vector regression (SVR) and decision tree (DT) algorithms using easily measurable soil properties. Results revealed that land use and soil type had significant effect on the WER. The highest mean WER was observed in Entisols with the lowest organic matter (OM), the lowest penetration resistance (PR) and the lowest aggregate mean weight diameter (MWD). Bare lands with the lowest OM and MWD showed the highest WER compared to other land uses. R2 and RMSE of the non-linear regression models developed based on the type of the relationship between the WER and easily measurable soil properties improved by 15% and 12%, respectively, compared to the linear regression model. In both train and test datasets, the SVR and DT models coupled to a genetic algorithm (GA) used for selecting the effective easily measurable soil properties had higher performance than the SVR and DT models using all easily measurable soil properties for predicting WER. With respect to statistical indices, the SVR model with R2 = 0.91 and RMSE = 0.68 g m−2 s−1 outperformed the MLR and DT for predicting the WER. We concluded that combining the SVR with GA could be an applicable and promising method for predicting WER.

Environmental changes in Yellow River Delta with terrace construction and agricultural cropping.

BackgroundCrude flats in delta areas are often saline–alkaline and unsuitable for agricultural cropping. In the 1990s, people residing in the Yellow River delta constructed terraces on the flats for agricultural development. Herein, we investigated environmental changes resulting from this agricultural development and evaluated whether the current land use is effective and sustainable.MethodsWe sampled soil and weeds from croplands, terrace slopes, and crude flats within the delta terrace landscape. The measured soil properties included soil salinity, pH, total N, total P, and organic matter in different lands and soil layers: 0–10, 10–20, and 20–30 cm. The surveyed weed characteristics were the biomass of roots and rhizomes, species composition, life form, cover and height. These indices were statistically verified by different land types and soil layers.ResultsSoil salinity in the terrace crop lands was found to have reduced to <4 g·kg−1, whereas in the crude flats, remained >6 g·kg−1. Soil pH in the terrace croplands was surprisingly increased to >9 ; meanwhile, organic matter content decreased drastically, which is significantly different from that observed in the case of terrace slopes and crude flats. Total N and P content in the terrace crop lands were seemingly unchanged on averages but at the depths >20 cm, they reduced unavoidably. Plant underground organs were relatively scarcer in the croplands than in the other lands. Weeds grew well on the terrace slopes but were insufficient in the croplands. Overall, terrace construction is effective for developing coastal saline flats for agricultural use, but the traditional land use in the Yellow River delta has caused chronic soil degradation that is against a sustainable productive industry.

Estimating soil chemical properties by diffuse reflectance spectroscopy: Promise versus reality

AbstractDiffuse reflectance spectroscopy in the visible and near‐infrared (VNIR) spectral range has increasingly been utilised in recent years to measure soil properties, including organic carbon and macronutrient content, cation exchange capacity, pH, and even trace metal concentration. Proponents have even suggested that conventional laboratory soil testing methods can ultimately be replaced by these less laborious and more rapid spectroscopic methods. However, to this point in time, reflectance spectroscopy has not demonstrated accuracy comparable to that of conventional physical–chemical testing methods. This review explains why correlations between VNIR spectral features and specific chemical properties within selected sets of soil samples are indirect at best and therefore cannot be trusted more universally to predict soil chemical properties in larger and less homogeneous sample sets. Because mathematical manipulation of the raw spectral data has become increasingly complex and obscure to the users, particularly when machine learning is employed, the possibility exists that the correlations found and the predictions made are based on chance relationships resulting from overfitting the spectral data to include random noise in addition to any real trends. It is concluded that, for real‐world soil testing for agronomic and environmental purposes (e.g. available nutrient and trace metal levels), spectral reflectance methods are not sufficiently reliable to replace conventional testing. Conversely, these reflectance methods show utility and convenience in measuring general trends across landscapes in levels of soil organic matter, carbonates, soluble salts and specific clay minerals.Highlights VNIR reflectance spectroscopy is reviewed as a method to measure soil properties. Estimating most soil chemical properties by VNIR relies on indirect or proxy correlations. Complex regression models used in predicting soil properties may overstate accuracy. Reflectance spectroscopy has lower reliability and extrapolability than conventional soil testing.

Soil water dynamics in drained and undrained meadows

Tile drainage belongs to one of the most important meliorative measures in the Czech Republic. It has been hypothesised that it may improve some soil properties which are influenced by the groundwater and their water regime. In the case of meadows, the used management method may also influence the soil properties. In this study, different physical soil properties (particle and bulk density, total soil porosity, maximum capillary water capacity, minimum air capacity, water retention capacity and saturated water content, volumetric water content and matric potential) at depths of 15, 35 or 40 and 60 cm in differently managed meadows (drained versus undrained) located near the village of Železná in the Czech Republic (mildly cold, humid climatic region) were investigated. The drained meadow is used mainly for grazing (extensively) and the undrained meadow is mown twice a year. In addition, the actual evapotranspiration was estimated for the 2018 vegetation season. The selected physical soil properties were significantly (P &amp;lt; 0.05) different between the experimental meadows, especially at depths of 0–28 versus 0–35 cm (particle and bulk density, total soil porosity, maximum capillary water capacity, water retention capacity and saturated water content) and 28–49 versus 35–45 cm (particle density, water retention capacity and saturated water content). In the case of all the studied soil depths, the volumetric water content and matric potential were significantly (P &amp;lt; 0.05) different between the experimental meadows in the years 2016–2019. The actual evapotranspiration was also significantly different (P &amp;lt; 0.05) between the meadows. The obtained differences in the measured soil properties and estimated actual evapotranspiration were probably influenced by the used tile drainage and also by the type of management of the meadow. It is necessary to obtain more research findings with respect to different types of management in the case of drained meadows and also undrained meadows to understand the role of both treatments (tile drainage, management).

Land management effects on wet aggregate stability and carbon content

AbstractLand management affects soil structure and many other soil properties and processes. Our objectives were to evaluate soil organic C (SOC), aggregate size distribution, aggregate‐associated C, and soil structure as affected by long‐term land management and slope. A chronosequence of 38 on‐farm sites with low to high (5–18%) slopes was selected to evaluate 5–40 yr of management. The sites were classified as business as usual (BAU) cropland (BAU‐Crop), BAU pasture (BAU‐Past), newly established conservation reserve program (CRP) areas (CRP‐New), and established CRP (CRP‐Old). Soil samples were collected from the 0‐to‐5‐ and 5‐to‐15‐cm depth increments and processed for soil property measurements including fractionation by wet sieving into five aggregate size classes (&gt;2,000, 1,000–2,000, 500–1,000, 250–500, and 53–250 μm). Within the surface 5 cm, mean weight diameter (MWD) and geometric mean diameter (GMD) were used to characterize soil structural stability. The BAU‐Past and CRP‐Old sites had 79% more macroaggregates (&gt;2,000, 1,000–2,000, and 500–1,000 μm), 123% higher MWD, 38% higher GMD, and 47% higher SOC than BAU‐Crop or CRP‐New sites. The 5‐to‐15‐cm depth increment showed a similar but lower magnitude response. Aggregate‐associated C was quantified using a constant soil mass that reflected aggregate size distribution to prevent overestimating C content. Lower‐slope locations had more SOC, more macroaggregates, more C associated with macroaggregates, and higher GMD and MWD compared with high‐slope locations across all management classifications and soil depths. The results support our hypothesis that the high‐slop soils may benefits from specific management decisions than the lower‐sloping soils as a function of landscape property. We recommend reestablishing grassland on sloping land that is susceptible to excessive soil erosion, although those practices will likely take a long time to restore soil structural stability and SOC content to precultivation levels.

Changes in Soil Prokaryotic Diversity in Response to Land-Use Changes in Sub-Saharan Africa

Sub-Saharan Africa is one of the most severely affected regions regarding soil degradation, a global issue with the loss of nutrients caused by inappropriate management, leading to low agricultural productivity. Here we asked the question of how soil prokaryotic communities are affected by shifts in land use management and subsequent losses in soil organic carbon. We sampled soils from three sites in Zambia which have neighboring natural and managed sites. After the measurement of soil properties, soil DNA was sequenced, targeting the 16S rRNA gene. As expected, total carbon in soil was decreased in the managed sites, with significant reductions of bacterial biomass. However, the diversity indices in the managed soils were higher than in natural soils. Particularly, the relative abundance of nitrifiers was increased in the managed soils, most likely as a result of fertilization. However also other bacteria, e.g., those which formed tight interactions with the cultivated crops including the genera Balneimonas, and Bacillus, were increased in the managed soils. In contrast bacteria belonging to the family Chloroflexi, which were high in abundance in the natural soil were outcompeted by other prokaryotes in the managed soils most likely as a result of changes in the amount of soil organic carbon. Overall, our results suggest that we need to discuss the trends of prokaryotic diversity separately from those for prokaryotic abundance. Even when bacterial abundances were decreased in the managed soils, nitrifiers’ relative abundance and diversity increased in our experiment, suggesting the possible alteration of the nitrogen cycle in managed soils in sub-Saharan Africa.

Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China.

Evaluating the bioavailability, bioaccessibility, and transferability of cadmium (Cd) in soil-grain-human systems is essential in areas with a Cd anomaly in the karst region of southwestern China. In the present study, the main controlling factors and prediction models for Cd transfer in a soil-grain-human system were investigated in a typical area where natural processes and anthropogenic activities interact in the karst region of southwestern China. The environmental availability of Cd (diethylenetriaminepentaacetic acid- and CaCl2 -extractable Cd [ ]) in the soil varies significantly because of the diversity of soil properties. However, Cd concentrations in the maize grain were significantly related only to the concentrations in the soil (r = 0.595, p < 0.01), indicating that soil is a good indicator for evaluating Cd uptake by maize grain. Of all the measured soil properties, the soil cation exchange capacity (CEC) and the soil calcium (Casoil ) were the most important factors influencing Cd accumulation in the soil-maize grain system. A transfer model combining , soil CEC, and Casoil was sufficiently reliable for predicting Cd accumulation in the maize grain (R2 = 0.505). Although there is room for improvement regarding the prediction performance of the chain model combining soil with Casoil to predict the bioaccessible Cd concentration in maize grain (R2 = 0.344 for the gastric phase and R2 = 0.356 for the gastrointestinal phase), our findings provide a useful reference to further explore a model that can be used for a relatively rapid and reliable estimation of dietary Cd exposure for specific regions prior to crop harvest. Environ Toxicol Chem 2021;40:2923-2934. © 2021 SETAC.

Calibrating SoilGen2 for interglacial soil evolution in the Chinese Loess Plateau considering soil parameters and the effect of dust addition rhythm

To better understand interglacial paleosol development by quantifying the paleosol development processes on the Chinese Loess Plateau (CLP), we need a soil genesis model calibrated for long timescales. Here, we calibrate a process-based soil genesis model, SoilGen2, by confronting simulated and measured soil properties for the Holocene and MIS-13 paleosols formed in the CLP for various parameter settings. The calibration was made sequentially on three major soil process formulations, including decalcification, clay migration and soil organic carbon, which are represented by various process parameters. The order of the tuned parameters was based on sensitivity analyses performed previously on the loess in West European and the CLP. After the calibration of the intrinsic soil process parameters, the effect of uncertainty of dust deposition rate on calibration results was assessed. Our results show that the simulated soil properties are very sensitive to ten reconstructed dust deposition scenarios, reflecting the propagation of uncertainty of dust deposition in model simulations. Our results also show the equal importance of calibrating soil process parameters and defining correct external forcings in the future use of soil models. Our calibrated model allows interglacial soil simulation in the CLP over long timescales.

Earthworm distributions are not driven by measurable soil properties. Do they really indicate soil quality?

Abundance and distribution of earthworms in agricultural fields is frequently proposed as a measure of soil quality assuming that observed patterns of abundance are in response to improved or degraded environmental conditions. However, it is not clear that earthworm abundances can be directly related to their edaphic environment, as noted in Darwin's final publication, perhaps limiting or restricting their value as indicators of ecological quality in any given field. We present results from a spatially explicit intensive survey of pastures within United Kingdom farms, looking for the main drivers of earthworm density at a range of scales. When describing spatial variability of both total and ecotype-specific earthworm abundance within any given field, the best predictor was earthworm abundance itself within 20-30 m of the sampling point; there were no consistent environmental correlates with earthworm numbers, suggesting that biological factors (e.g. colonisation rate, competition, predation, parasitism) drive or at least significantly modify earthworm distributions at this spatial level. However, at the national scale, earthworm abundance is well predicted by soil nitrate levels, density, temperature and moisture content, albeit not in a simple linear fashion. This suggests that although land can be managed at the farm scale to promote earthworm abundance and the resulting soil processes that deliver ecosystem services, within a field, earthworm distributions will remain patchy. The use of earthworms as soil quality indicators must therefore be carried out with care, ensuring that sufficient samples are taken within field to take account of variability in earthworm populations that is unrelated to soil chemical and physical properties.

Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring

Abstract. Information on soils' composition and physical, chemical and biological properties is paramount to elucidate agroecosystem functioning in space and over time. For this purpose, we developed a national Swiss soil spectral library (SSL; n=4374) in the mid-infrared (mid-IR), calibrating 16 properties from legacy measurements on soils from the Swiss Biodiversity Monitoring program (BDM; n=3778; 1094 sites) and the Swiss long-term Soil Monitoring Network (NABO; n=596; 71 sites). General models were trained with the interpretable rule-based learner CUBIST, testing combinations of {5,10,20,50, and 100} ensembles of rules (committees) and {2, 5, 7, and 9} nearest neighbors used for local averaging with repeated 10-fold cross-validation grouped by location. To evaluate the information in spectra to facilitate long-term soil monitoring at a plot level, we conducted 71 model transfers for the NABO sites to induce locally relevant information from the SSL, using the data-driven sample selection method RS-LOCAL. In total, 10 soil properties were estimated with discrimination capacity suitable for screening (R2≥0.72; ratio of performance to interquartile distance (RPIQ) ≥ 2.0), out of which total carbon (C), organic C (OC), total nitrogen (N), pH and clay showed accuracy eligible for accurate diagnostics (R2&gt;0.8; RPIQ ≥ 3.0). CUBIST and the spectra estimated total C accurately with the root mean square error (RMSE) = 8.4 g kg−1 and the RPIQ = 4.3, while the measured range was 1–583 g kg−1 and OC with RMSE = 9.3 g kg−1 and RPIQ = 3.4 (measured range 0–583 g kg−1). Compared to the general statistical learning approach, the local transfer approach – using two respective training samples – on average reduced the RMSE of total C per site fourfold. We found that the selected SSL subsets were highly dissimilar compared to validation samples, in terms of both their spectral input space and the measured values. This suggests that data-driven selection with RS-LOCAL leverages chemical diversity in composition rather than similarity. Our results suggest that mid-IR soil estimates were sufficiently accurate to support many soil applications that require a large volume of input data, such as precision agriculture, soil C accounting and monitoring and digital soil mapping. This SSL can be updated continuously, for example, with samples from deeper profiles and organic soils, so that the measurement of key soil properties becomes even more accurate and efficient in the near future.

A Comparative Study of Conceptual Model Complexity to Describe Water Flow and Nitrate Transport in Deep Unsaturated Loess

AbstractUnderstanding nitrate migration through the deep vadose zone is essential for aquifer vulnerability assessments. The effect of variability of physical properties of the deep vadose zone on nitrate transport has been scarcely explored. Recently, deep nitrate storage profiles were determined in the vadose zone of the Loess Plateau of China. Using these observations along with measured soil properties, this study investigates the effect of loess vertical heterogeneity on water movement and nitrate transport through the deep vadose zone. Models of different complexity were established and calibrated. First, a simple piston flow and nitrate mass balance approach was calibrated to the observed nitrate storage. The results indicate that the total nitrate storage is estimated well, while the estimation of the distribution of nitrate is relatively poor. Subsequently, Richards' equation and the Advection‐Dispersion equation were evaluated. Three different conceptualizations of the numerical models were calibrated against deep vadose zone nitrate and water content observations: (1) one‐layer model assuming homogenous loess vadose zone; (2) a model that considers a hydraulic conductivity (Ks) decay function and (3) a model where the Miller‐Miller scaling factors are prescribed to account for changes of the hydraulic functions with depth. Accounting for the vertical Ks decay in the numerical models improved water flow performances. The study reveals the adequacy of implementing water flow and nitrate transport numerical models together with a simple representation of the vertical loess variability, for simulating nitrate migration in loess deep vadose zone environments.

Visual soil examination and evaluation in the sub-humid and semi-arid regions of Kenya

Soil quality is indicated by the interaction of physical, chemical and biological soil properties. The importance of physical properties, for example soil structure, lies in the fact that they enhance chemical and biological soil functions. Consequently, periodic assessment of structural quality is an important aspect of soil quality management. Quantitative soil properties can be used as indirect indicator parameters for soil structural changes. However, measuring these properties is not applicable, especially for smallholder farmers who cannot afford to pay for laboratory tests. This study contributes to the validation of visual field assessments by comparing the performance of such methods on ‘tropical’ soils. The study was conducted across two regions with contrasting soil types and land use, in the sub-humid with clay Nitiosl and semi-arid with sandy loam Cambisol locations of Kenya. At both locations, visual methods were tested on soils under cropland and under natural forests (NF). Under the cropland, evaluation sites were selected from researcher and farmer managed sites. Visual scores from visual soil assessment (VSA), visual evaluation of soil structure (VESS) and visual evaluation of soil structure using the core (coreVESS) were correlated with soil physical and chemical properties measured in the laboratory. Under the clay Nitisol, absolute values of Pearson r between VSA scores and laboratory measured soil properties ranged from 0.84 to 0.54, for VESS, they varied between 0.75 and 0.37 while for coreVESS, they ranged from 0.84 to 0.60. For the sandy loam Cambisol, absolute Pearson r values between laboratory measured soil properties and VSA scores ranged from 0.83 to 0.29, the r values were between 0.88 and 0.45 for VESS and between 0.81 and 0.40 for coreVESS. From the obtained correlations, we concluded that the visual methods tested are capable of distinguishing structural quality due to different land use and are therefore suitable for assessing soil structural quality of tropical soils in Africa. Management thresholds were determined using bulk density (BD). The target value for good soil quality (Sq<2) for the Kibugu Nitisol was BD = 0.0012*SOC+0.6476 (r = 0.71; SOC is soil organic carbon), while the trigger and remediation values were 0.93 Mg m−3 (Sq = 2) and 0.99 Mg m−3 (Sq = 3), respectively. In the absence of SOC data, the target mean BD for Sq<2 is 0.79 Mg m−3. For Machang’a Cambisol, the target, trigger and remediation values were 1.48 Mg m−3 (Sq = 2), 1.56 Mg m−3 (Sq = 3) and 1.64 Mg m−3 (Sq = 4), respectively.

Myths and misconceptions related to unsaturated soil mechanics

There have been three main pillars associated with the development of an applied engineering science for both saturated and unsaturated soil mechanics; namely, i) the synthesis of continuum mechanics theories of physical behavior, ii) the laboratory measurement of relevant soil properties, and iii) analyses that illustrate the solution of practical example problems. Geotechnical engineers have, however, been relatively slow in adopting unsaturated soil mechanics into geotechnical engineering practice. There have been several so-called “myths or misconceptions” that appear to have hindered the application of unsaturated soil mechanics. This paper attempts to describe and dispel what are deemed to be misconceptions related to the more general implementation of unsaturated soil mechanics into engineering practice. The so-called “myths” come from the acceptance of false information related to unsaturated soil behavior and a hesitancy to embrace changes to existing empirical protocols. Several misconceptions are identified in the paper that are related to: i) complexity of unsaturated soil mechanics theories, ii) inability to readily measure soil suctions in-situ, iii) the nonlinearity of unsaturated soil property functions, iv) permanency of soil suctions above the water table, v) difficulties associated with assessing ground surface moisture flux conditions, and vi) difficulties associated with numerical modeling that involves solving nonlinear partial differential equations. Each of the above-mentioned items are dealt with as myths or misconceptions in the sense of being impediments to the application of unsaturated soil mechanics in geotechnical engineering practice.